A method for detecting stents in medical images is already known from the publication entitled “Deformable Boundary Detection of Stents in Angiographic Images”, by Ioannis Kompatsiaris et alii, in IEEE Transactions on Medical Imaging, Vol. 19, no 6, June 2000, pages 652-662. This document describes an image processing method for deformable boundary detection of medical tools, called stents, in angiographic images.
A stenosis is a narrowing of a blood vessel. When a stenosis is identified in a coronary artery of a patient, a procedure called angioplasty or Percutaneous Transluminal Coronary Angioplasty (PTCA) may be prescribed. A basic idea of PTCA is to position a monorail with a small inflatable balloon within a narrowed section of an artery. The balloon is inflated in order to push outwards against the wall of the narrowed artery. This process reduces the narrowing until it no longer interferes with the blood flow. The balloon is then deflated and removed from the artery. In order to avoid re-stenosis to occur, said process is often followed by a stent implantation. A stent is a surgical stainless steel coil that is introduced in the artery on another balloon monorail. The stent is wrapped tightly around the balloon attached to the monorail. Said balloon tipped monorail is introduced into the artery. The inflation of the balloon causes the stent to expand, pressing it against the artery wall. The stent, once expanded, can be considered as a permanent implant, which acts like a scaffold keeping the artery wall open and allowing normal blood flow to occur through the artery. Stent placement helps many patients avoid emergency heart bypass interventions and/or heart attacks.
A key step of said procedure is to check whether the stent has been placed at the right position of the stenosis and whether it has been successfully expanded. As a matter of fact, clinical problems are associated with inadequate placement or expansion of the stent. Inadequately expanded stents can locally disrupt blood flow and cause thrombosis.
During a PTCA it is possible to observe in real time the area of the stenosis in a sequence of angiographic images, but the precise stent placement is not easily visible for several reasons:                the image sequence is rather noisy and its contrast is low due to the use of a low X-Ray dose,        the stent location changes all along the image sequence due to the influence of cardiac pulses and the patient's breathing.Studies revealed that, consequently, more than eighty per cent of stents might be insufficiently dilated despite an apparently successful deployment in the sequence of angiographic images. Automatic detection of the stent border could, therefore, help to achieve a more precise checking of the stent placement.        
The method that is disclosed in the cited publication relies on the identification of the stent in the angiographic images. It comprises the steps of:                forming 3D models of stents,        deriving a set of 2D models using perspective rules,        matching said 2D models with real angiographic images in a training phase,        roughly detecting a stent in an angiographic image using the set of 2D models and maximum likelihood criteria,        refining the borders of the roughly detected stent using an active contour model.        
A drawback of said method is that it presents a calculation load that is actually too heavy for real time processing of a sequence of images in the intervention phase of stent implantation.